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Concurrency & performance

asyncio, threading, multiprocessing, and profiling-friendly performance patterns.

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Concurrency & performance easy

How to Convert Data in Parallel with ThreadPoolExecutor in Python

This example demonstrates converting a list of items in parallel using ThreadPoolExecutor, showing performance gains over serial processing.

concurrency threadpoolexecutor parallelism
Python 
import time
from concurrent.futures import ThreadPoolExecutor


def convert_data(item):
    """Simulate a CPU/IO-bound conversion task."""
    time.sleep(0.05)  # simulate work
    return item.upper()


if __name__ == "__main__":
    items = [f"item_{i}" for i in range(20)]

    start = time.perf_counter()
    serial_…
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